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Knowledge Base Completion

Knowledge base completion is the task which automatically infers missing facts by reasoning about the information already present in the knowledge base. A knowledge base is a collection of relational facts, often represented in the form of "subject", "relation", "object"-triples.

Papers

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Showing 31–40 of 156 papers

TitleStatusHype
Combining Rules and Embeddings via Neuro-Symbolic AI for Knowledge Base Completion—0
Exploiting Structured Knowledge in Text via Graph-Guided Representation Learning—0
Feature-Rich Networks for Knowledge Base Completion—0
DOCENT: Learning Self-Supervised Entity Representations from Large Document Collections—0
An Interpretable Knowledge Transfer Model for Knowledge Base Completion—0
Distributional Negative Sampling for Knowledge Base Completion—0
Distributed Prediction of Relations for Entities: The Easy, The Difficult, and The Impossible—0
Combining Representation Learning with Logic for Language Processing—0
Augmenting Compositional Models for Knowledge Base Completion Using Gradient Representations—0
Embedding Cardinality Constraints in Neural Link Predictors—0
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